The System for the Creation of Random
Electronic Adaptive Music (s.c.r.e.a.m.) is a
framework for the generation and synthesis of random music. Based on the
experimental work of John Cage, Karlheinz Stockhausen, and others who questioned
and helped reformulate the definition of music, the system allows for the
generation of any possible genre of music.

The s.c.r.e.a.m. will interpret predefined probabilistic models and use them to
influence the structure of the music it creates. These models can be easily
configured, so that the type of music the system creates can be easily modified.
The s.c.r.e.a.m. is made up of several smaller components; this modularity
allows for further easy modification of the system's functionality. The
framework allows for an arbitrary number of instruments to be used; the
instruments themselves are open-ended and therefore any collection of sounds can
be implemented as an instrument. This allows for almost endless possibilities.
The system also allows for an arbitrary number of environmental sensors that
can modify the music.

The framework of the s.c.r.e.a.m. will be written in mainly C and C++,
conforming to C99 and ISO C++ standards. It will be structured as a set of
extensible libraries, furthering modularity and allowing easy design
modification.

This project seeks to create the s.c.r.e.a.m. and a simple implementation of it.
This simple implementation will use the s.c.r.e.a.m. framework to create simple
music of a single genre using a small number of instruments. It will have a few
environmental sensors; one of these will be a microphone that can add sounds
from the environment into the music. Once completed, the finished project will
produce simple musical output that can be easily recognized as music.

Experimental, or avant-garde, music is a very loose term for music that lies
at or outside the boundary of traditional music. Artists who have ventured
into this category include John Cage, Karlheinz Stockhausen, Philip Glass,
Pierre Boulez, and many others. John Cage, probably the most well-known
experimental musician, experimented in "chance music" [1],
which refers to music where different elements, such as a particular note, are
determined purely by chance. Cage was also prolific for his other works of
experimental music; the most famous of these was his piece titled 4'33", which
was 273 seconds of silence. More important than the music developed by
composers like Cage, Stockhausen, and others, though, were the ideas behind
their music; Cage, specifically, expressed the opinion that music could be any
collection of sounds, and commonly gave performances where random audience noise
was meant to be the actual music. These ideas can be summed up simply in a
couple quotations by Cage and Stockhausen:

"The first question I ask myself when something doesn't seem to be beautiful is,
`why do I think it's not beautiful?' And very shortly you discover that there
is no reason."

In the past fifty years, electronic music has become a mainstream concept.
After the introduction of instruments like the electronic keyboard in the
1960s, musicians like Jean-Michel Jarre and Karlheinz Stockhausen began to
experiment with electronically-created music [2,3].
In the late 1960s and 1970s, synthesizers like the Moog and Minimoog
provided a much cheaper way for musicians to incorporate electronic sounds in
music, and they were quickly adopted and used by such artists and groups as
The Monkees, The Beatles, Miles Davis, and Herbie Hancock, in addition to
countless others. Now, in 2008, electronic instruments can be found in nearly
every musical setting, from esoteric avant-garde studio productions to
commercial jingles and advertisements to video game music.

With the recent advent of powerful computing systems, Cage's ideas of "chance
music" can be implemented on a much greater scale than flipping coins to
determine melodies. Over the last twenty years, several musical systems
implemented on computers incorporating a random element have been designed and
put into action. The iMUSE system, created by LucasArts developers Michael Land
and Peter McConnell in the early 1990s [4], was a music system for
video games that synchronized the music with visual action. Dr. Ulf
Berggren, of Uppsala Universitat, developed a system that used a random
process to create random sonatas modeled after those of Mozart [5].
A few patents have been filed on music generation systems, but no commercial
music generation systems exist [6,7,8].

Although exploratory work has been done in the field of random music generation,
none of these systems provide a truly abstract system for creating any type of
random music. Dr. Berggren's system generates sonatas; this is a small subset
of a single genre of music. While this sonata-generation system is useful, a
more useful system would be one that was not restricted to generating sonatas,
but instead could generate any kind of music.

The System for the Creation of Random
Electronic Adaptive Music (s.c.r.e.a.m.)
exists to fill this void. The project seeks to create a
framework for a completely open-ended random music generation system. This
system is meant to be able to generate any genre of music and have as few
boundaries as possible limiting what is generated. The system is also meant to
be adaptive; it should include the ability of the music to adapt to its
environment using external sensors. The system is meant to be as modular as
possible, so that each component of the system can be interchanged with another
at will. Overall, s.c.r.e.a.m. is an open-ended tool aspiring to
the ideals of experimental musicians like John Cage, Karlheinz Stockhausen, and
others.

However, it should be noted that the s.c.r.e.a.m. is a framework, and unless it
is implemented and configured properly, it will not produce anything that sounds
like today's definition of music. Therefore, this project encompasses the
construction of the s.c.r.e.a.m. framework, as well as a simple implementation
to demonstrate its usefulness and abilities.

The s.c.r.e.a.m., as its name implies, is a system for the automatic generation
of random music that is affected by its environment. While the s.c.r.e.a.m.
itself is merely a framework and not an implementation, this project seeks to
design the framework as well as provide an implementation. A list of
straightforward design goals for the s.c.r.e.a.m., given that the objectives are
the construction of the framework and a simple implementation.

Use a small number of `instruments', or sound collections, to
synthesize the music

Be clearly affected by its environment and sensor input

Include a microphone that uses an adaptive filter (described below)

The aforementioned microphone functions as a microphone that captures samples
of the external environment and plays them back in the music. It will need to
use an adaptive filter to filter out its own output from the voice sensor's
input; otherwise, the system will produce feedback and be unstable.

The long-term goals of this project are not to create a particular kind of
musical application, but to create a framework in which many different kinds
of musical applications can be developed. To make this a reality, the
components of the system should be as basic as possible and have well-defined
interfaces between them. This is so that in the future it will be possible to
combine already-built components in new ways and create new components to
interface with these. Then, many different kinds of musical tools can be
created with minimum effort.

This will be realized primarily by creating the project as a collection of
small programs that talk to each other through various kinds of binary FIFOs,
which could be pipes, files, or network sockets. Good software design practices
must also be adhered to; documentation of every detail of the framework must be
extensive and accurate. This modular approach with extensive documentation will
help to ensure and extend the usefulness of the system.

The simple implementation of the s.c.r.e.a.m. proposed for this project includes
a microphone. This sensor would record sound from the environment, and play
it back through the system. However, problems arise when this input is in the
same environment that the system's output is being played into. The system's
output will produce an unstable feedback loop, which is certainly undesirable.
The solution choosen to combat this problem is an adaptive filter, which will
eliminate the system's output from the voice sensor's input and remove the
unstable feedback effects.

To truly tailor the music to its surroundings, a simple microcontroller-based
sensor module that communicates with the host computer via a serial port will
be developed. The numerical textual data this creates will be processed by the
system and influence the music being produced according to preconfigured
probability models.

One environmental sensor has already been created and used by one of the
project's engineers in the past [9]. This sensor is a humidity
sensor, and will be retooled for use as a s.c.r.e.a.m. sensor.

The design of the s.c.r.e.a.m. framework, as discussed earlier, is intended to
be as modular as possible. This design paradigm lets a developer replace one
component of the s.c.r.e.a.m. with another, with minimal effort. Following this
design idea, a top-level abstraction of the s.c.r.e.a.m. can be seen in Figure
1.

Figure 1:
Top-level abstraction of s.c.r.e.a.m.

It can be seen in Figure 1 that the "brain" is the controlling
unit of the entire system. It accepts input from any number of sensor modules,
and the sensor inputs affect the output of the brain. The brain determines the
structure of the music (components including current chord, current musical
structure, form, tempo, and suggested rhythms) and sends this information to
each instrument (denoted "Inst."). The number of instruments is arbitrary.
Once each instrument uses the information given by the brain to determine what
rhythms and tones it is going to play, it sends this information to its
synthesizer (denoted "Synth.") and it is turned into PCM audio. This can then
be sent to either an effects processing module (denoted "Effects") or directly
to an output mixer. An effects processing module would modify the PCM audio
stream in any way, and output the modified PCM audio to either another effects
processing module or a mixer. A mixer's function is simple; it takes all the
PCM audio inputs it is getting and turns them into one composite PCM output.
Then, this output can either be saved to a file, played over speakers, or any
number of other possibilities. Any number of mixers in a single system is
possible. This has interesting implications; for example, one brain could be
simultaneously controlling four isolated music performances.

The modularity of this system allows for nearly endless possibilities for the
output of the system. With any number of possible instruments, completely
different musical ensembles can be constructed; for instance, the system could
be using the instruments of an entire orchestra, or, on the other hand, it could
be using only an accordion and a kazoo. The instruments do not even have to be
known instruments; they are just a collection of synthesizable sounds, so any
conceivable set of sounds can be used as an instrument.

The proposed simple implementation of the s.c.r.e.a.m. will follow the top-level
abstraction found in Figure 1. The system will have only one
mixer. It will accept PCM audio from a minimal set of instruments, being
controlled by one brain configured to produce simple output that is recognizable
as music.

The system will also have a voice sensor with an adaptive filter, used for
simultaneous playback and recording, as discussed earlier. A simple design
abstraction for the adaptive filter system to be used with the voice sensor can
be seen in Figure 2.

Figure 2:
Schematic of adaptive filter system.

In this filter design, the output of the system is fed back into the filter.
The filter coefficients are then determined such that when the filter is
convoluted with the microphone's input, the music output is filtered out of the
microphone's input.

Because the modular approach chosen for s.c.r.e.a.m., multiple small programs
are being created instead of one large multithreaded application. This
approach prevents the rapid sharing of data structures in memory and creates
the necessity for an interprocess communication system. Many methods have been
devised over the years to handle different kinds of communication between
processes on the same or different systems, in real time or asynchronously.

Since the system is meant to be as close to real time as permissible while
still maintaining its modular and network transparent architecture, any method
chosen for interprocess communication should make minimum latency a high
priority. While shared memory has the least latency, it also is the least
easily extended to network architectures and asynchronous operation. Named
pipes allow a convenient method for local interprocess communication, and can
be substituted with files when an asynchronous method is desired. Also, they
are easily tunneled through network sockets, allowing network transparent
operation.

A simple library, scream_ipc, has been designed to handle interprocess
communication though named pipes, sockets, and files. By creating a data type,
scream_pipe_t, that represents an individual bidirectional data
link, and two functions that operate on this, named pipe_send and
pipe_receive, it becomes possible to write backends that operate
using sockets, named pipes, pre-generated files, or any other method that may
be implemented in the future. This is in line with the modular approach of the
s.c.r.e.a.m. framework; a developer could easily rewrite the code of the
scream_ipc library to modify its behavior without needing to rewrite
any of the other components of the s.c.r.e.a.m. framework.

Most of the modules in the s.c.r.e.a.m. are fairly straightforward. The mixer
mixes music; instruments take musical information and produce music; sensors
take environmental data and send this information to the brain. However, the
brain itself is a complicated structure.

On the most basic level, using the specifications put forth in the top-level
abstraction, the brain takes environmental data and past output and uses those
to generate musical information, which it sends to each individual instrument.

However, this concept must be elaborated on for this project's implementation of
the brain. The planned implementation will use detailed probabilistic models to
compose and modify the music. These models will be contained in simple text
files, and will contain probabilities of the form

This gives the probability of the event given any number of conditions
through . However, the list of probabilities is of an arbitrary
length, so a full probability tree for each event and condition
cannot be created. Therefore, the brain will need to use statistical inference
to estimate the probabilities it has not been given.

This method of statistical inference allows for incredibly simple as well as
intensely complicated probabilistic models defined in configuration files.

C and C++ have been chosen as the primary programming languages for the project,
with Bash shell scripts being used to assemble the components into a working
system at runtime and tear down the components at exit. The target compilers
for the C and C++ code will be the GNU Compiler Collection (gcc) version 4,
though conformity to C99 and ISO C++ standards for the code, to maximize
portability, is highly desirable. Building will be entirely automated with GNU
Make, and revision control will be handled by the Concurrent Versioning System
(CVS).

It is intended that the s.c.r.e.a.m. framework will use as few third-party or
external libraries as possible. Therefore, the only third-party libraries to
be linked against by the vast majority of the s.c.r.e.a.m. code should be the C
and C++ standard libraries and POSIX system libraries. However, it would still
be useful to use a third-party library for final-stage audio output and mixing.
Candidates for a library to be used for this are the JACK Audio Connection Kit
(JACK) and the Simple Directmedia Layer (SDL). Through abstractions in the
s.c.r.e.a.m. code, changing the audio output library being used should be a
trivial task.

The coding standards being followed will have the same strict commitment to
modularity as the system as a whole. Any calls to third-party library
functions will be wrapped with functions or classes that hide any pecularities
of the third-party system behind a common abstraction that can be maintained
even if the back-end library is changed.

Portability is also a concern; as a result, the data types of all interfaces
will be expressed in terms of types defined in stdint.h, which defines
types in terms of signedness and bit width (for example, uint8_t is
defined as an 8-bit unsigned integer). stdint.h was chosen because it
is part of the standard C and C++ libraries. However, stdint.h makes
no guarantee of byte order. This could lead to complications with network
interaction between machines with different endiannesses. This incompatibility
is noted, but ignored due to the overwhelmingly Intel-centric development
environment. A solution to this problem would be to convert all integer data in
all data structures transmitted and received into network order; however, this
process adds considerable overhead and complexity to an otherwise seamless task,
so it will not be done.

There is a significant number of tradeoffs involved in creating a system the
size of the s.c.r.e.a.m., many of which affect the design of the project deeply.
The fundamental specifications of the design were an effective guide in
determining which path to take at each step of the design process. From the
inception of the ideas behind the s.c.r.e.a.m., the goal has been a modular and
loosely cooperating collection of independent processes and not a single
monolithic process. The ability to operate transparently over network
connections further fed into the decision to create s.c.r.e.a.m. as a
constellation of programs instead of a single program, and was a primary factor
in the decision to use first-in-first-out (FIFO) data structures for
interprocess communication.

The work flow described in Figure 3 breaks down the development of
the s.c.r.e.a.m. into weeks and tasks. Weeks are assigned capital letters
beginning with the week of January 20 and skipping the week of March 16, which
is assigned an asterisk instead. The final two weeks are referred to by symbols
and will not be used for active project development. Lowercase letters are
assigned to tasks, which are either independent or lumped into one of three
broad categories. These tasks are:

a.

Define and document all interfaces.

b.

Develop basically functional interprocess communication
library.

c.

Develop an audio output library.

d.

Develop a simple sample-based synthesizer.

e.

Devise a format for sample sets for the sample-based
synthesizer.

f.

Develop a synthesizer that plays sound from the microphone
without feedback.

g.

Develop a minimal instrumentalist.

h.

Develop a theoretical basis for the brain.

i.

Define a file format for the brain's probability tables.

j.

Write a minimal probability table for the brain.

k.

Develop and code the brain.

l.

Add hooks for sensor input to the brain.

m.

Build a simple sensor with a serial interface on a
protoboard.

n.

Test and adjust the prototypical system.

The major milestones in the development of the s.c.r.e.a.m. are the moments
when new combinations of components can be tested and heard. The first such
milestone will be in the week of February 17 when the sample-based synthesizer
is ready for testing with a simple instrumentalist to drive it. After that, in
the week of February 24, the playback of sound processed from a microphone input
without audible feedback will provide another checkpoint. By the weekend of
March 2, the s.c.r.e.a.m. should make its first completely autonomous sounds.
From then on, the development team's only goals are to improve the quality
of the music produced and provide more ways for it to be controlled.

Demonstration and evaluation of the s.c.r.e.a.m. is simple and complicated at
the same time. To prove that the system works and is functional, one merely
needs to run it and listen to the output, and from there, determine if it is
music. However, in-depth evaluation of the s.c.r.e.a.m. is not so easy. Since
the system depends heavily on random values, testing particular pieces of the
system is unreliable. If, for example, the effect of the sensors on the music
wanted to be shown, one might consider changing the sensor's input drastically.
Unfortunately, though, this might not always change the music, since the system
could randomly decide to ignore the sensor's input at that point in time.

Instead, quantitative evaluation of the s.c.r.e.a.m. as a whole requires
probability analysis over time. Metrics would need to be designed to measure
the music, and would need to be recorded over time. Sensor stimuli would also
need to be recorded and measured over time. This process is tedious and
difficult, and therefore will not be attempted in this project to evaluate the
system.

A better approach to evaluating the system is instead to examine each individual
component. For example, to evaluate the brain, the musical data being sent to
each instrument should be observed. Again, this will be hard to make
conclusions about because it depends on a random element. However, components
like the synthesizers and the mixer should be much easier to evaluate, since
there is no random element in those particular components. Therefore, this
method of examining each module in the s.c.r.e.a.m. will be used to evaluate its
performance.

Qualitative evaluation of the system, though, will be performed by the simple
act of listening to the output. If this output satisfies the design goals
established earlier for this project's particular implementation of the
s.c.r.e.a.m., then the project can be classified as successful.

As a project with primarily aesthetic goals, the s.c.r.e.a.m. does not strive
to be marketable in the same sense that an ingot of copper or a loaf of bread
are marketable, or even in the same sense that a violin is marketable. What the
s.c.r.e.a.m. provides is unique form of expression and a set of tools to
accomplish that expression, most of which exist only as software, and are thus
freed from any of the physical restrictions associated with tangible items.

The opportunity to experience the s.c.r.e.a.m. on some level is an inalienable
right granted to anyone with a functioning set of ears. Anyone who listens to
the sound generated by the s.c.r.e.a.m. is devoting a portion of their
resources to processing this data, and is therefore the only kind of customer
the s.c.r.e.a.m. has a desire to create. Others may take it upon themselves to
obtain the source code and create their own derivative works based on the
s.c.r.e.a.m., thus devoting their resources to enhancing the project. These
customers are on a different level, and obtaining them requires a method of
spreading knowledge of the project.

The primary method of marketing the s.c.r.e.a.m. is simply allowing people to
hear the music it produces. The easiest way to do that is to perform it; devote
computing resources to it and allow it to play on speakers that are within
earshot of large numbers of people. If people who are capable hear it and
understand its source, they will want to obtain the s.c.r.e.a.m. for themselves
and perhaps even augment it. Therefore, if it is successful, the most powerful
marketing tool for the s.c.r.e.a.m. is the s.c.r.e.a.m. itself.

Free sample parts that were already on hand will be used to create a sensor
system on a breadboard that had already been obtained for other purposes.
Computers that would have already been running anyway will be used for project
development and testing. Therefore, the cost of the physical components used to
make up the s.c.r.e.a.m. rests at an easy zero dollars.

THE ORANGE LUNCHBOX BRIGADE, a team of two engineers, will work
tirelessly to complete the s.c.r.e.a.m. by the set deadlines. As believers in
their own product, they hedge their ability to profit on its success. Because of
this, they believe it is only fair for all profit produced by s.c.r.e.a.m. to be
split evenly between them.

The System for the Creation of Random
Electronic Adaptive Music (s.c.r.e.a.m.) is an
open-ended system for the generation of random, environmentally-modified music.
Inspired partially by the ideas of John Cage, Karlheinz Stockhausen, and other
leading experimental musicians, the system is meant to be able to create any
sort of music, even that which is currently considered outside the realm of
traditional music.

By using a simple top-level abstraction, the s.c.r.e.a.m. framework can be split
into four basic parts: the brain, the instruments, the environmental sensors,
and the mixer. The brain uses the input sent by the environmental sensors as
well as the previous output of the entire system to decide on the structure,
form, tempo, rhythm, and chordal structure of the music. This information is
given to each of the instruments, who in turn decide the exact notes and rhythms
that they will play, based on the sent information. These notes and rhythms are
then synthesized and sent to the mixer, which mixes all of the sounds to produce
one sound output.

It should be noted that any number of mixers, instruments, environmental
sensors, and even brains can be used. This allows for endless possibilities in
instrumentation, performance, and composition of the music.

The s.c.r.e.a.m. framework will be a collection of libraries written mainly in C
and C++. The code will conform as closely as possible to C99 and ISO C++
standards, to make the system portable to almost any computing environment.
Each module of the system (brain, instruments, sensors, and mixers) will be a
standalone process which communicates with all the other processes.

However, this project also encompasses the simple implementation of the
s.c.r.e.a.m. framework. This implementation will create simple music of a
specified genre, using a few simple instruments, one mixer, one brain, and a
couple environmental sensors. A humidity sensor has already been designed and
could be used for this purpose. Another planned sensor is a microphone;
however, since the microphone will be in the same environment as the music is
being played in, an adaptive filter must be used to cancel out any possible
feedback effects so that the system will not become unstable.

Overall, the s.c.r.e.a.m. framework will provide a limitless platform for the
generation of random music. Depending on the implementation of the system, it
could be used to create engulfing orchestral works like Vivaldi's `The Four
Seasons', or revolutionary artistic works like Miles Davis' `Bitches Brew', or
even bizarre experimental music like Karlheinz Stockhausen's
`Helikopter-Streichquartett'. However, the real beauty of the system lies in
its open-endedness; it is capable, in theory, of designing music far outside the
bounds of what human ears comprehend as music. The possibilities are endless.